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Characterisation and prediction of carbohydrate content in zucchini fruit using near infrared spectroscopy
Author(s) -
PomaresViciana Teresa,
MartínezValdivieso Damián,
Font Rafael,
Gómez Pedro,
del RíoCelestino Mercedes
Publication year - 2017
Publication title -
journal of the science of food and agriculture
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.782
H-Index - 142
eISSN - 1097-0010
pISSN - 0022-5142
DOI - 10.1002/jsfa.8642
Subject(s) - partial least squares regression , starch , fructose , chemistry , principal component analysis , sucrose , carbohydrate , food science , standard error , sugar , mathematics , biochemistry , statistics
BACKGROUND Zucchini fruit plays an important part in healthy nutrition due to its high content of carbohydrates. Recent studies have demonstrated the feasibility of visible–NIRS to predict quality profile. However, this procedure has not been applied to determine carbohydrates. RESULTS Visible–NIR and wet chemical methods were used to determine individual sugars and starch in zucchini fruits. By applying a principal component analysis (PCA) with NIR spectral data a differentiation between the less sweet versus the sweetest zucchini accessions could be found. For the determination of carbohydrate content effective prediction models for individual sugars such as glucose, fructose, sucrose and starch by using partial least squares (PLS) regression have been developed. CONCLUSION The coefficients of determination in the external validation ( R 2 VAL) ranged from 0.66 to 0.85. The standard deviation (SD) to standard error of prediction ratio (RPD) and SD to range (RER) were variable for different quality compounds and showed values that were characteristic of equations suitable for screening purposes. From the study of the MPLS loadings of the first three terms of the different equations for sugars and starch, it can be concluded that some major cell components such as pigments, cellulose, organic acids highly participated in modelling the equations for carbohydrates. © 2017 Society of Chemical Industry